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Posted to issues@spark.apache.org by "ASF GitHub Bot (JIRA)" <ji...@apache.org> on 2018/12/16 22:32:00 UTC
[jira] [Commented] (SPARK-24398)
SQLAppStatusListener.aggregateMetrics() invocation is too slow
[ https://issues.apache.org/jira/browse/SPARK-24398?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16722599#comment-16722599 ]
ASF GitHub Bot commented on SPARK-24398:
----------------------------------------
srowen closed pull request #21438: [SPARK-24398] [SQL] Improve SQLAppStatusListener.aggregateMetrics() too slow
URL: https://github.com/apache/spark/pull/21438
This is a PR merged from a forked repository.
As GitHub hides the original diff on merge, it is displayed below for
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diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/ui/SQLAppStatusListener.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/ui/SQLAppStatusListener.scala
index d254af400a7cf..1ef93abbccdff 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/ui/SQLAppStatusListener.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/ui/SQLAppStatusListener.scala
@@ -159,7 +159,7 @@ class SQLAppStatusListener(
}
private def aggregateMetrics(exec: LiveExecutionData): Map[Long, String] = {
- val metricIds = exec.metrics.map(_.accumulatorId).sorted
+ val metricIds = exec.metrics.map(_.accumulatorId).toSet
val metricTypes = exec.metrics.map { m => (m.accumulatorId, m.metricType) }.toMap
val metrics = exec.stages.toSeq
.flatMap { stageId => Option(stageMetrics.get(stageId)) }
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> SQLAppStatusListener.aggregateMetrics() invocation is too slow
> ---------------------------------------------------------------
>
> Key: SPARK-24398
> URL: https://issues.apache.org/jira/browse/SPARK-24398
> Project: Spark
> Issue Type: Improvement
> Components: Web UI
> Affects Versions: 2.3.0
> Reporter: furongbin
> Priority: Major
>
> RROR 18/05/24 14:08:25 AsyncEventQueue: Dropping event from queue appStatus. This likely means one of the listeners is too slow and cannot keep up with the rate at which tasks are being started by the scheduler. [dag-scheduler-event-loop]
> WARN 18/05/24 16:39:54 AsyncEventQueue: Dropped 208205 events from appStatus since Thu May 24 16:30:57 CST 2018. [dag-scheduler-event-loop]
> WARN 18/05/24 16:40:19 SQLAppStatusListener: agregateMetrics cost=18.6s, metricIds.size=775, metrics.size=5292940, aggregatedMetrics=615 [pool-22-thread-1]
> private def aggregateMetrics(exec: LiveExecutionData): Map[Long, String] = {
> val metricIds = exec.metrics.map(_.accumulatorId).sorted
> val metricTypes = exec.metrics.map
> { m => (m.accumulatorId, m.metricType) }
> .toMap
> val metrics = exec.stages.toSeq
> .flatMap \{ stageId => Option(stageMetrics.get(stageId)) }
> .flatMap(_.taskMetrics.values().asScala)
> .flatMap \{ metrics => metrics.ids.zip(metrics.values) }
> {color:#ff0000}val aggregatedMetrics = (metrics ++ exec.driverAccumUpdates.toSeq){color}
> {color:#ff0000} .filter \{ case (id, _) => metricIds.contains(id) }{color}
> .groupBy(_._1)
> .map
> { case (id, values) => id -> SQLMetrics.stringValue(metricTypes(id), values.map(_._2).toSeq) }
> if (exec.metricsValues != null)
> { exec.metricsValues }
> else
> { aggregatedMetrics }
> }
> *Case:*
> when aggregatedMetrics.size=5000000, metrics.size=1000, then the execution({color:#ff0000}val aggregatedMetrics = (metrics ++ exec.driverAccumUpdates.toSeq){color}
> {color:#ff0000}.filter \{ case (id, _) => metricIds.contains(id) }{color}) is very slow
>
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